Lung cancer is the leading cause of cancer related death worldwide (18%) with 1.2 million new cases reported annually. Despite 36% to 71% of lung cancer patients receiving radiotherapy, and continuous efforts to improve treatment outcomes, the 5-year survival rate is only 16%. These patients urgently need better treatment techniques and tools to improve survival rates.
An increase in tumor dose of 1-Gy results in a 4% improvement in survival. On the other hand, a 1-Gy decrease in overall mean lung dose results in a 2% reduction in pneumonitis. It is clear from these statistics that better targeted radiotherapy has the potential to improve treatments outcomes. Image-guided radiotherapy (IGRT) has been used to simultaneously increase tumor dose while minimizing the dose to the surrounding healthy tissue.
IGRT is used by more than 93% of radiation oncologists in the United States. However, imaging techniques such as MRI, PET, CT and CBCT are blurry or contain artifacts when there is significant respiratory motion. As a consequence, it is difficult for a radiotherapist to accurately position a lung tumor patient for treatment, which increases the likelihood that some of the radiation that is targeted at the tumor will irradiate healthy lung tissue.
FIG. 1a shows a diagram of the projection geometry for CBCT imaging showing the first (P1) projection and ith (Pi) projection. The gantry rotates around the target at a constant velocity with a constant pulse rate between projections. FIG. 1b shows a photograph of a linear accelerator used in radiotherapy with the on-board-imager.
Two of the most common imaging techniques used by radiotherapists for IGRT are CT and CBCT imaging. CT images are obtained by taking projections in a plane, or slice, then moving the gantry forward a small distance where the process is repeated. Once a number of slices have been taken across the anatomy the slices are reconstructed into a 3D image. Alternatively, some CT systems take projections in a continuous helical motion rather than using slices. CT images are usually of a higher quality when compared to CBCT images so CT imaging is usually used for diagnostic and treatment planning purposes. CBCT differs from CT in that the gantry, containing the X-ray source and detector, is rotated around the anatomy during which a series of cone shaped projections are taken (see FIG. 1b). The projections are then reconstructed using the Feldkamp-Davis-Kress (FDK) algorithm to give a 3D view of the patient's anatomy.
CBCT images can be obtained in the treatment room using the OBI's attached to linear accelerators and are used in the treatment room by radiotherapists to position their patients for treatment.
4DCT imaging provides a video, or movie, of the 3D geometry. The motion of the heart, abdomen, prostate, lungs and tumor can be observed over time. To acquire 4DCT images of the lungs, the respiratory cycle is separated into respiratory bins such as inhale limit, exhale limit and at different stages between the two limits. A full set of slices are collected in each respiratory bin so that a four dimensional view of the changing anatomy can be obtained. Two techniques are commonly used to acquire 4DCT images in practice: (1) Prospective where you wait until the patient's breathing is in the desired region then acquire a slice before moving the couch for the next slice and repeating the process. (2) Retrospective where you acquire data for all phases of the respiratory cycle by oversampling the dataset and then retrospectively allocating slices to respiratory bins.
It has been shown that lung tumors typically move 0.5 to 1 cm, and as much as 5 cm, during the breathing cycle. Artifacts are not entirely eliminated by 4DCT imaging. It has been observed that at least one artifact exists in 90% of 4DCT images of the diaphragm and heart. Despite the problems associated with respiratory motion, there has been a significant increase in 4DCT imaging since it was first published. In 2009, usage of 4DCT was over 44% in the United States with a continuous upwards trend.
CBCT images are obtained by taking between 120 and 600 evenly spaced projections. For each projection, a cone shaped beam is emitted by the source and the attenuation of the beam is recorded by the detector (see FIG. 1a). The gantry is rotated around the patient at a constant angular velocity, which for safety reasons is limited to 6°/s, and an X-ray pulse rate of around 0.2 seconds is used. Total imaging time can be around 1 or 2 minutes, which depends on the desired number of projections and the velocity of the gantry.
For smaller targets, such as arms, head and neck, it is possible to use full fan projections where the beam is the full cone shape. This can reduce imaging time as the gantry only needs to rotate 180° plus the angular width of the cone. In most practical applications, such as the abdomen, half fan projections are used where the gantry rotates the full 360°.
Once all of the projections have been collected, image reconstruction algorithms are used to reconstruct a 3D view of the target. The FDK algorithm is the most popular algorithm used to reconstruct images. Image reconstruction can be a slow process that can take several minutes to reconstruct a single image. Total Variation and Tight Frame methods have been implemented to reconstruct images using Graphics Processing Units (GPU's). In addition to the computation time improvements obtained using a GPU, these methods show promise at reducing the number of projections to below 100 and therefore reducing the radiation dose to the patient.
Image quality is better if the projections are evenly spaced in gantry angle; see the polar plot in FIG. 2a for an example of good projection spacing. However, when respiratory motion is involved, projections are taken at different stages during the respiratory cycle; see the polar plot in FIG. 2b where numbers (1), (2) and (3) are used to identify projections taken at inhale limit, exhale limit and mid inhale. The resulting image is likely to contain artifacts, or the image will be blurry, in the region where significant respiratory motion takes place.
4DCBCT imaging attempts to produce images showing the motion of the lungs, and tumor, during the breathing cycle. This is achieved by collecting a full set of projections in a number of respiratory bins; the projections in the polar plot of FIG. 2c give an example of projections taken only from the inhale limit respiratory bin. Within each respiratory bin, there is limited anatomical motion, so blurring and artifacts in the resulting images are reduced. Three-dimensional images are reconstructed in each respiratory bin and a video is created showing a 4D view of the anatomy. Commercial systems use a constant gantry angular velocity with a constant X-ray pulse rate and post-process projections into respiratory bins. However, as can be seen in the polar plot in FIG. 2c, if the gantry is rotated around the patient with a constant angular velocity the angular separation between projections is not ideal and projection clustering occurs.
There have been some attempts to handle respiratory motion by accounting for motion in the image reconstruction algorithms. Motion compensated CBCT uses estimates of respiratory motion to reconstruct an image. Taking this approach further, some researchers have attempted to modify the image reconstruction algorithms to look for a stationary component with a separate periodic component. These methods assume that the patient's breathing is regular so the algorithms are likely to have difficulty reconstructing an image if the patient's breathing is irregular.
One of the evolving image-guidance methods to account for lung cancer motion during each treatment session, with applications in liver, pancreas and other thoracic/abdominal malignancies, is 1st generation four-dimensional cone beam computed tomography (4DCBCT). The projection images and respiratory signal are synchronously acquired and post-processed into respiratory correlated phase bins, such as end-inhale, mid-inhale, etc.
However, in the current implementation there is no communication between the respiratory signal and image acquisition. This results in bunched angular projections, with the CBCT images suffering from poor image quality and streak artifacts. The poor quality limits the use of current images for online guidance and anatomic and functional adaptation.
Common to all current 4DCBCT systems is the use of a constant angular velocity of the gantry. The gantry is rotated around the patient at a much slower rate than for 3DCBCT imaging. After the projections have been collected, they are compared with the recorded breathing trace and then post-processed into respiratory bins. The aim is to collect enough projections in each respiratory bin, with relatively even angular separation, to reconstruct an image. However, the use of a constant angular velocity results in clustering of projections.
As an example of projection clustering consider the left plot in the top row of FIG. 3a where a sinusoidal breathing wave is given for a patient with a 15 hz (cycles per minute) breathing rate.
FIGS. 3a-3d show examples of clustered and missing projections with a sinusoidal breathing pattern at 15 hz. In row (1) the patient's breathing wave is shown with displacement on the vertical axis and time on the horizontal axis where the breathing cycle is separated into 10 displacement bins. The percentages listed are the approximate percentage of time spent in each displacement bin. The (1), (2) and (3) vertical lines correspond to projections that are allocated to respiratory bins 1, 5 and 8 respectively. The polar plots show the gantry angles at the projections taken in respiratory bins 1 (1), 5 (2) and 8 (3) with a constant gantry velocity of 1:5°/s.
The x-axis tick marks of FIG. 3a correspond to the time at which a projection is taken if a pulse rate of 0.2 s is used. The projections corresponding to displacement bins 1, 5 and 8 are marked as (1), (2) and (3) respectively. If the gantry is rotated with an angular velocity of 1.5°/s and a projection is taken every 0.2 seconds there will be 1200 projections in total taken over 4 minutes. If the displacement bin at exhale limit is analyzed (1), then either 4 or 5 projections, with an angular separation of 0.9° to 1.2°, will be taken in the 0.82 seconds at exhale limit. The patient's breathing will not enter the exhale limit respiratory bin for a further 3.18 seconds in which time the gantry moves 4.77°. This process will be repeated with a cluster of 4 or 5 projections followed by a gap of at least 4.77° before the next cluster of projections. A polar plot showing the gantry angle for each projection in displacement bin 1 is the exhale limit (1) polar plot in FIG. 3b. In total there will be 240 projects in 60 clusters if 4 projections are taken per respiratory bin. In the worst case scenario there will be 5 projections per respiratory bin resulting in 300 projections in displacement bin 1.
Clustering of projections results in a higher radiation dose to the patient for a small improvement in image quality.
The (2) polar plot in FIG. 3c, for displacement bin 5, shows an example of missed projections. Even though the polar plot has an excellent angular separation between projections, only one projection exists per respiratory cycle. The patient has received a radiation dose from 60 projections but there are not enough projections to reconstruct an image of suitable quality. This problem occurs because only 0.13 seconds is spent in displacement bin 5 during inhale and a further 0.13 seconds during exhale. A 0.2 second projection pulse rate can miss the displacement bin altogether. In the example, a projection is taken during exhale but not during inhale. In practice the displacement bin can be missed during both inhale and exhale in consecutive cycles leading to large gaps between projections. In the worst case, the respiratory bin could be missed during both inhale and exhale resulting in no projections allocated to respiratory bin 5.
The polar plot (3) in FIG. 3d shows a situation that is between the polar plots (1) and (2). A projection is taken during both inhale and exhale, resulting in 120 projections in total, but the projections are unevenly spaced. For displacement bin 8 there may be enough projections to reconstruct an image, but if the projections were more evenly spaced fewer projections would be required to obtain an image with comparable quality.
Because projections are post-processed into respiratory bins, first generation methods are unable to adapt if the patient's breathing is irregular as no feedback with the patient's respiratory data is used to regulate the gantry. Therefore image quality is likely to be poor if the patient's breathing is irregular.
What is needed is a method that improves the angular separation of projections in each respiratory bin in real-time during 4DCBCT imaging.